The presence of solute concentration fluctuations at spatial scales much below the scale of resolution is a major challenge for modeling reactive transport in porous media. Overlooking small-scale fluctuations, which is the usual procedure, often results in strong disagreements between field observations and model predictions, including, but not limited to, the overestimation of e˙ective reaction rates. Existing innovative approaches that account for local reactant segregation do not provide a general mathematical formulation for the generation, transport and decay of these fluctuations and their impact on chemical reactions. We propose a Lagrangian formulation based on the random motion of fluid particles carrying solute concentrations whose departure from the local mean is relaxed through multi-rate interaction by exchange with the mean (MRIEM). We derive and analyze the macroscopic description of the local concentration covariance that emerges from the model, showing its potential to simulate the dynamics of mixing-limited processes. The action of hydrodynamic dispersion on coarse-scale concentration gradients is responsible for the production of local concentration covariance, whereas covariance destruction stems from the local mixing process represented by the MRIEM formulation. The temporal evolution of integrated mixing metrics in two simple scenarios shows the trends that characterize fully-resolved physical systems, such as a late-time power-law decay of the relative importance of incomplete mixing with respect to the total mixing. Experimental observations of mixing-limited reactive transport are successfully reproduced by the model.

Here we present an ~2000 year high-resolution glaciochemical record from the South Pole. Significant changes in chemical concentrations, accumulation rate, stable water isotopes and deuterium excess records are captured during the period ~1400-1700 CE, indicating a reorganization of atmospheric circulation that occurred in two steps: ~1400-1425 CE and ~1650-1700 CE. Major declines in dust and SO42- concentrations are observed ~1400 CE suggesting poleward contraction of the southern circumpolar vortex and potential intensification of westerly air flow, accompanied by a sea ice decrease in the Weddell Sea and potentially also in the Indian sector of the Southern Ocean. The changes in stable water isotopes, deuterium excess, NO3- concentration and accumulation rate characterize a second shift in atmospheric reorganization between 1650-1700 CE, reflecting increased marine air mass intrusions and subsequent reduction of the katabatic winds, and a shift to a colder moisture source for South Pole precipitation. These internally consistent changes involving atmospheric circulations and sea ice conditions are also in line with those identified for the recent period, and include associations with the large-scale teleconnections of El Niño Southern Oscillation (ENSO) and the Southern Annular Mode (SAM).

The severity and frequency of wildfires have risen dramatically in recent years, drawing attention to the term ‘wildland-urban interface’ (WUI), the region where man-made constructions meet flammable vegetation. Herein, we mapped a finer-scale, novel linear WUI for California (CA) based on the intersection of boundaries of wildland vegetation and building footprint. The direct intersection is referred to as a direct WUI, whereas the intersection at 100-m is known as an indirect WUI. More fires were ignited closer to direct WUI than indirect WUI due to their proximity to communities. However, the overlap of past fire perimeters with indirect WUI is greater than that with direct WUI which shows that more areas were burned in the indirect WUI due to embers transported by strong wind gusts during large wildfires. The study’s findings will help land managers and policymakers in controlling fire dangers, land-use planning, and reducing threats to fire-prone communities.

Of immediate widespread concern is the accelerating transition from Holocene-like weather patterns to unknown, and likely unstable, Anthropocene patterns. A fell example is irreversible Arctic phase change. It is not clear if existing AOGCMs are adequate to model anticipated global impacts in detail; however, the GISS ModelE AOGCM can be used to locally compare and extend the PIOMAS Arctic ocean historical ice-volume dataset into the near future. Arctic Amplification (AA) mechanisms are poorly understood; to enable timely results, a simple linear, Arctic TOA grid-boundary energy-input is used to enforce AA, avoiding the perils of arbitrary modification of relatively well-studied parameterizations (e.g., restriction of cloud-top height to induce local warming). Only PIOMAS springtime/max and fall/min Arctic ice-volume decadal, linear trends were enforced. This temporally-broad grid-boundary modification produces a surprisingly detailed consonance with 10 out of 12 temporal profiles falling within 1-sigma of PIOMAS temporal data for the entire history modeled (2003 to 2021). The data are then integrated to 2050. The result is a zero-ice-volume, summer/fall half-year, beginning ca. 2035 (onset 1-sigma of ± ~5 years), with mean annual Arctic temperatures increasingly trending above freezing. Persistent, Arctic phase change follows this half-year transition about 20 years later. Also present in later stages, the 500 hPa height minimum is no longer nearly-coincident with the pole, suggesting jet stream disruption and its consequences. Hypothesized large clathrate-methane releases likely associated with Arctic temperature and phase change are also examined. A basic assumption is that the Arctic ice (i.e., temperature) must be preserved at all costs. This work establishes a reasonably detailed timeline for the Arctic phase change based on well-studied AOGCM physics, slightly tuned to decades of PIOMAS data. This result also points to the Arctic as a key, near-term site for localized, nondestructive intervention to mitigate Arctic phase change (e.g., Stjern [2018]), thereby slowing the Holocene -> Anthropocene growing-season disruption. Although such an intervention cannot itself accomplish the requirements of the IPCC SP-15 [2018], nor Planetary Boundaries theory, delaying the Arctic phase change will likely extend the time-window for accomplishing those critical tasks and ultimately to at least slow the rate of increase of climate emergencies.

Satellite observations of tropical maritime convection indicate an afternoon maximum in anvil cloud fraction that cannot be explained by the diurnal cycle of deep convection peaking at night. We use idealized cloud-resolving model simulations of single anvil cloud evolution pathways, initialized at different times of the day, to show that tropical anvil clouds formed during the day are more widespread and longer lasting than those formed at night. This diurnal difference is caused by shortwave radiative heating, which lofts and spreads anvil clouds via a mesoscale circulation that is largely absent at night, when a different, longwave-driven circulation dominates. The nighttime circulation entrains dry environmental air that erodes cloud top and shortens anvil lifetime. Increased ice nucleation in more turbulent nighttime conditions supported by the longwave cloud top cooling and cloud base heating dipole cannot overcompensate for the effect of diurnal shortwave radiative heating. Radiative-convective equilibrium simulations with a realistic diurnal cycle of insolation confirm the crucial role of shortwave heating in lofting and sustaining anvil clouds. The shortwave-driven mesoscale ascent leads to daytime anvils with larger ice crystal size, number concentration, and water content at cloud top than their nighttime counterparts.

Chemical data acquired by Curiosity’s Alpha Particle X-ray Spectrometer (APXS) during examination of the contact between the upper Mount Sharp group and overlying Stimson formation sandstones at the Greenheugh pediment reveal compositional similarities to rocks encountered earlier in the mission. Mount Sharp group strata encountered below the Basal Siccar Point group unconformity at the base and top of the section, separated by >300 m in elevation, have distinct and related compositions. This indicates enhanced post-depositional fluid flow and alteration focused along this contact. Sandstone targets exposed immediately above the unconformity have basaltic compositions consistent with previously encountered eolian Stimson formation sandstones, except at the contact, where they show the addition of S. Resistant sandstone outcrops above the contact have higher K, Mn and Na and lower Ni concentrations that primarily reflect changes in provenance. They are compositionally related to cap rock float blocks encountered as Curiosity climbed through the Mount Sharp group, and Bradbury group sandstone outcrops. The higher K, pediment sandstones are interpreted to have a similar provenance to some Bradbury group sandstones, further evidence for widespread, alkaline source rock within and/or in the vicinity of Gale crater. The Bradbury and Siccar Point groups may both be younger than the Mount Sharp group. Alternatively, an alkaline source area in and around Gale crater has been eroded by both water and wind at different times (both before and after deposition of the Mount Sharp group), during the evolution of the crater and its infill.

Dynamic modeling of sequences of earthquakes and aseismic slip (SEAS) provides a self-consistent, physics-based framework to connect, interpret, and predict diverse geophysical observations across spatial and temporal scales. Amid growing applications of SEAS models, numerical code verification is essential to ensure reliable simulation results but is often infeasible due to the lack of analytical solutions. Here, we develop two benchmarks for three-dimensional (3D) SEAS problems to compare and verify numerical codes based on boundary-element, finite-element, and finite-difference methods, in a community initiative. Our benchmarks consider a planar vertical strike-slip fault obeying a rate- and state-dependent friction law, in a 3D homogeneous, linear elastic whole-space or half-space, where spontaneous earthquakes and slow slip arise due to tectonic-like loading. We use a suite of quasi-dynamic simulations from 10 modeling groups to assess the agreement during all phases of multiple seismic cycles. We find excellent quantitative agreement among simulated outputs for sufficiently large model domains and small grid spacings. However, discrepancies in rupture fronts of the initial event are influenced by the free surface and various computational factors. The recurrence intervals and nucleation phase of later earthquakes are particularly sensitive to numerical resolution and domain-size-dependent loading. Despite such variability, key properties of individual earthquakes, including rupture style, duration, total slip, peak slip rate, and stress drop, are comparable among even marginally resolved simulations. Our benchmark efforts offer a community-based example to improve numerical simulations and reveal sensitivities of model observables, which are important for advancing SEAS models to better understand earthquake system dynamics.

Recent breakthroughs in artificial intelligence (AI), and particularly in deep learning (DL), have created tremendous excitement and opportunities in the earth and environmental sciences communities. To leverage these new ‘data-driven’ technologies, however, one needs to understand the fundamental concepts that give rise to DL and how they differ from ‘process-based’, mechanistic modelling. This paper revisits those fundamentals and addresses 10 questions often posed by earth and environmental scientists with the aid of a real-world modelling experiment. The overarching objective is to contribute to a future of AI-assisted earth and environmental sciences where DL models can (1) embrace the typically ignored knowledge base available, (2) function credibly in ‘true’ out-of-sample prediction, and (3) handle non-stationarity in earth and environmental systems. Comparing and contrasting earth and environmental problems with prominent AI applications, such as playing chess and trading in stock markets, provides critical insights for better directing future research in this field.

The unequal spatial distribution of ambient nitrogen dioxide (NO2), an air pollutant related to traffic, leads to higher exposure for minority and low socioeconomic status communities. We exploit the unprecedented drop in urban activity during the COVID-19 pandemic and use high-resolution, remotely-sensed NO2 observations to investigate disparities in NO2 levels across different demographic subgroups in the United States. We show that prior to the pandemic, satellite-observed NO2 levels in the least white census tracts of the United States were nearly triple NO2 levels in the most white tracts. During the pandemic, the largest lockdown-related NO2 reductions occurred in urban neighborhoods that have 2.0 times more non-white residents and 2.1 times more Hispanic residents than neighborhoods with the smallest reductions. NO2 reductions were likely driven by the greater density of highways and interstates in these racially and ethnically diverse areas. Although the largest reductions occurred in marginalized areas, the effect of lockdowns on racial, ethnic, and socioeconomic NO2 disparities was mixed and, for many cities, non-significant. For example, the least white tracts still experienced ~1.5 times higher NO2 levels during the lockdowns than the most white tracts experienced prior to the pandemic. Future policies aimed at eliminating pollution disparities will need to look beyond reducing emissions from only passenger traffic and also consider other collocated sources of emissions such as heavy-duty trucks, power plants, and industrial facilities.

Fossil fuel combustion, land use change and other human activities have increased the atmospheric carbon dioxide (CO2) abundance by about 50% since the beginning of the industrial age. The atmospheric CO2 growth rates would have been much larger if natural sinks in the land biosphere and ocean had not removed over half of this anthropogenic CO2. As these CO2 emissions grew, uptake by the ocean increased in response to increases in atmospheric CO2 partial pressure (pCO2). On land, gross primary production (GPP) also increased, but the dynamics of other key aspects of the land carbon cycle varied regionally. Over the past three decades, CO2 uptake by intact tropical humid forests declined, but these changes are offset by increased uptake across mid- and high-latitudes. While there have been substantial improvements in our ability to study the carbon cycle, measurement and modeling gaps still limit our understanding of the processes driving its evolution. Continued ship-based observations combined with expanded deployments of autonomous platforms are needed to quantify ocean-atmosphere fluxes and interior ocean carbon storage on policy-relevant spatial and temporal scales. There is also an urgent need for more comprehensive measurements of stocks, fluxes and atmospheric CO2 in humid tropical forests and across the Arctic and boreal regions, which are experiencing rapid change. Here, we review our understanding of the atmosphere, ocean, and land carbon cycles and their interactions, identify emerging measurement and modeling capabilities and gaps and the need for a sustainable, operational framework to ensure a scientific basis for carbon management.

We present in situ observations of near‐bed velocity profiles with high temporal and spatial resolution from a Nortek Vectrino Profiler deployed in South San Francisco Bay. Using Hilbert analysis, we ensemble‐averaged near‐bed velocity profiles by wave phase and calculated wave phase‐dependent boundary layer thickness for varying wave and current conditions. We also applied mixing length relationships to derive a boundary layer thickness‐based eddy‐viscosity and compared this estimate to one obtained from the k–ɛ turbulence model. From the eddy viscosity estimates, we find that while turbulence responds instantaneously to shear, boundary layer thickness lags by a scaling estimate based on the turbulence response timescale. This analysis provides a method for wave‐phase decomposition of field‐based velocity profile time series and shows that there is a finite‐time response between turbulence dissipation and boundary layer thickness.

We study how the vertical distribution of relative humidity (RH) affects climate sensitivity, even if it remains unchanged with warming. Using a radiative-convective equilibrium model, we show that the climate sensitivity depends on the shape of a fixed vertical distribution of humidity, tending to be higher for atmospheres with higher humidity. We interpret these effects in terms of the effective emission height of water vapor. Differences in the vertical distribution of RH are shown to explain a large part of the 0 to 30% differences in clear-sky sensitivity seen in climate and storm-resolving models. The results imply that convective aggregation reduces climate sensitivity, even when the degree of aggregation does not change with warming. Combining our findings with relative humidity trends in reanalysis data shows a tendency toward Earth becoming more sensitive to forcing over time. These trends and their height variation merit further study.

Beamforming determines the quality of received signal by an antenna array using Signal-to-Noise-Interference Ratio (SINR) in cellular base stations. This paper will help in the installation of current heterogeneous wireless networks. Here, adaptive BF is implemented on the Machine Learning (ML) platform. The applicable ML methods to estimate the SINR of Multiple-Input-Multiple-Output (MIMO-mm-Wave) 5G wireless network are explored. The significant BF features are used in predicting the SINR. The cross-validation experiment is performed to assess the robustness of the best predictive method. The performance analysis parameters’ result shows the maximum value of accuracy, in value having the acceptable error on the data set.

Juno Microwave Radiometer (MWR) observations of Jupiter’s mid-latitudes reveal a strong correlation between brightness temperature contrasts and zonal winds, confirming that the banded structure extends throughout the troposphere. However, the microwave brightness gradient is observed to change sign with depth: the belts are microwave-bright in the p<5 bar range and microwave-dark in the p>10 bar range. The transition level (which we call the jovicline) is evident in the MWR 11.5 cm channel, which samples the 5-14 bar range when using the limb-darkening at all emission angles. The transition is located between 4 and 10 bars, and implies that belts change with depth from being NH3-depleted to NH3-enriched, or from physically-warm to physically-cool, or more likely a combination of both. The change in character occurs near the statically stable layer associated with water condensation. The implications of the transition are discussed in terms of ammonia redistribution via meridional circulation cells with opposing flows above and below the water condensation layer, and in terms of the ‘mushball’ precipitation model, which predicts steeper vertical ammonia gradients in the belts versus the zones. We show via the moist thermal wind equation that both the temperature and ammonia interpretations can lead to vertical shear on the zonal winds, but the shear is ~50x weaker if only NH3 gradients are considered. Conversely, if MWR observations are associated with kinetic temperature gradients then it would produce zonal winds that increase in strength down to the jovicline, consistent with Galileo probe measurements; then decay slowly at higher pressures.

The mechanical deformation of sea ice has substantial influence over large-scale (e.g., > 10 km) ice properties, such as the ice thickness distribution, as well as small-scale (e.g., < 50 m) features, including leads and ridges. The conditions leading to sea ice fracture are frequently studied in the context of a uniform ice sheet. Natural sea ice, however, is highly heterogeneous and riddled with flaws. Failure occurs primarily as brittle fracture localized in space and time where stresses, and strain rates, locally exceed failure criteria. Here we seek to better understand the mechanical deformation and fracture of sea ice under such typical field conditions. In particular, we aim to characterize how forces propagate across an approximately 1 km^2 heterogeneous domain by observing the stress-strain field in an ice floe at resolutions required to capture pre-fracture elastic strains. The combination of instruments deployed allow a detailed view of the formation, propagation, parting, and subsequent shearing of a fracture in natural sea ice, providing field evidence of modes of failure in compressive shear. The relatively low change in stress observed within meters of the fracture location highlights the need for further research into disparities in sea ice strength measurements at laboratory and field scales. The ability of this system to capture strain concentration zones and to detect initial fracture hours prior to lead formation indicates the potential for predicting areas at high risk for fracture in an on-ice operational setting.

Sea ice pressure ridges have been recognized as important locations for both physical and biological processes. Thus, understanding the associated light-field is crucial, but their complex structure and internal geometry render them hard to study by field methods. To calculate the in- and under-ridge light field, we combined output from an ice mechanical model with a Monte-Carlo ray tracing simulation. This results in realistic light fields showing that light levels within the ridge itself are significantly higher than under the surrounding level ice. Light guided through ridge cavities and scattering in between ridge blocks also results in a more isotropic ridge-internal light field. While the true variability of light transmittance through a ridge can only be represented in ray tracing models, we show that simple parameterizations based on ice thickness and macro-porosity allow accurate estimation of mean light levels available for photosynthesis underneath ridges in field studies and large-scale models.

We present new results using data collected by the Poker Flat Incoherent Scatter Radar (PFISR) of energy transfer rates which include the effects from neutral winds in the high latitude E-region ionosphere-thermosphere (IT) during Fall 2015. The purpose of our investigation is to understand the magnetic local time (MLT) dependence of the peak energy transfer, which occurs asymmetrically in the morning-evening (dawn-dusk) MLT sector. The statistical characteristics of both altitude-resolved and altitude-integrated energy transfer rates in the auroral E region local to PFISR during different geomagnetic conditions are quantified. Our analysis shows that the geomagnetic activity level has a large impact on the energy transfer rates. In contrast with previous investigations, we find both the altitude integrated electromagnetic (EM) energy transfer rate and Joule heating rate are larger in the evening sector than in the morning sector during all geomagnetic activity conditions. We also observe non-negligible negative EM energy transfer rates below 110 km in the morning sector during active conditions, which is associated with neutral winds during this MLT interval. The statistical results show that the neutral winds tend to increase the Joule heating rate in a narrow altitude range in the morning sector and impact a broader region with respect to altitude and time in the evening sector in the E region under moderate and active conditions. We find that during quiet conditions that the neutral winds have a significant contribution to the Joule heating and contribute up to 75% of the Joule heating. However, during active conditions, the enhanced fields are a dominant driver of Joule heating, while the neutral wind effects can reduce the Joule heating rates by 25% or more relative to the passive heating rates.

This study focuses on determining the orientation and constraining the magnitude of the present-day stress in the Dezful Embayment in Iran’s Zagros Fold and Thrust Belt. Two datasets are used: the first includes petrophysical data from 25 wells (3 to 4 km), and the second contains 108 earthquake focal plane mechanisms mostly occurring in blind active basement faults (5 to 20 km). Formal stress inversion analysis of the focal plane mechanism demonstrates that the major basement faults are reverse faults with ( =2.0-2.2). The seismologically determined SHmax direction is 37{degree sign}{plus minus}10{degree sign}, nearly perpendicular to the strike of most faults in the region. However, borehole geomechanics analysis using rock strength and drilling evidence leads to the counterintuitive result that the shallow state of stress is a normal/strike-slip regime. These results are consistent with the low seismicity level in the sedimentary cover in the Dezful Embayment, and may be evidence of stress decoupling due to the existence of salt layers. This finding also aligns with the Mohr-Coulomb faulting theory in that the N-S strike-slip basement Kazerun fault has an unfavourable orientation for slip in a reverse fault regime with an average SW-NE SHmax orientation. The stress state situation in the field was used to identify the optimally oriented fault planes and the fault friction factor. The results are useful for determining the origin of seismic activity in the basin and better assessing fault-associated seismic hazards in the area.